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A sampling model of social judgment.

Mirta Galesic1, Henrik Olsson1, Jörg Rieskamp2

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Social judgments like false consensus and uniqueness arise from cognitive processes interacting with social environments. The new social sampling model (SSM) quantifies these judgments, explaining self-enhancement and self-depreciation patterns.

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Area of Science:

  • Social Psychology
  • Cognitive Science
  • Computational Social Science

Background:

  • Social judgment research lacks a unified framework for phenomena like false consensus and self-enhancement.
  • Existing models struggle to explain diverse social judgment outcomes cohesively.

Purpose of the Study:

  • To propose and test a new process model, the social sampling model (SSM), for social judgments.
  • To provide a parsimonious quantitative account for phenomena like false consensus, false uniqueness, self-enhancement, and self-depreciation.

Main Methods:

  • Developed the social sampling model (SSM) based on memory sampling of social instances.
  • Tested SSM predictions against empirical data concerning social environments and judgment biases.
  • Analyzed the influence of environmental factors like homophily and question format on judgment outcomes.

Main Results:

  • The SSM successfully explains how cognitive sampling interacts with environmental structures to produce social judgments.
  • Demonstrated that homophily levels and question formats predict whether false consensus or false uniqueness emerges.
  • The model accounts for previously unexplained patterns in self-enhancement and self-depreciation.

Conclusions:

  • The social sampling model offers a unified, quantitative explanation for diverse social judgment phenomena.
  • Environmental factors and cognitive sampling are key determinants of social judgments and self-perceptions.
  • Understanding immediate social circles is crucial for evaluating broader social environments and one's position within them.